[Retracted] Taxonomy of Adaptive Neuro‐Fuzzy Inference System in Modern Engineering Sciences
Adaptive Neuro‐Fuzzy Inference System (ANFIS) blends advantages of both Artificial Neural
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …
An efficient binary chimp optimization algorithm for feature selection in biomedical data classification
Accurate classification of high-dimensional biomedical data highly depends on the efficient
recognition of the data's main features which can be used to assist diagnose related …
recognition of the data's main features which can be used to assist diagnose related …
A tri-stage wrapper-filter feature selection framework for disease classification
In machine learning and data science, feature selection is considered as a crucial step of
data preprocessing. When we directly apply the raw data for classification or clustering …
data preprocessing. When we directly apply the raw data for classification or clustering …
A novel hybrid gene selection for tumor identification by combining multifilter integration and a recursive flower pollination search algorithm
M Li, L Ke, L Wang, S Deng, X Yu - Knowledge-Based Systems, 2023 - Elsevier
Gene selection is crucial to tumor identification based on microarray expression data. The
identification of genes with strong discriminative power has been a hot research topic and a …
identification of genes with strong discriminative power has been a hot research topic and a …
[HTML][HTML] A study of bio-inspired computing in bioinformatics: a state-of-the-art literature survey
AK Mandal, PKD Sarma… - The Open …, 2023 - openbioinformaticsjournal.com
Background: Bioinspired computing algorithms are population-based probabilistic search
optimization approaches inspired by biological evolution and activity. These are highly …
optimization approaches inspired by biological evolution and activity. These are highly …
Hybrid binary COOT algorithm with simulated annealing for feature selection in high-dimensional microarray data
Microarray analysis of gene expression can help with disease and cancer diagnosis and
prognosis. Identification of gene biomarkers is one of the most difficult issues in microarray …
prognosis. Identification of gene biomarkers is one of the most difficult issues in microarray …
Hybrid binary arithmetic optimization algorithm with simulated annealing for feature selection in high-dimensional biomedical data
Gene expression data play a significant role in the development of effective cancer
diagnosis and prognosis techniques. However, many redundant, noisy, and irrelevant genes …
diagnosis and prognosis techniques. However, many redundant, noisy, and irrelevant genes …
Gene selection using hybrid dragonfly black hole algorithm: A case study on RNA-seq COVID-19 data
This paper introduces a new hybrid approach (DBH) for solving gene selection problem that
incorporates the strengths of two existing metaheuristics: binary dragonfly algorithm (BDF) …
incorporates the strengths of two existing metaheuristics: binary dragonfly algorithm (BDF) …
Biomarker identification and cancer survival prediction using random spatial local best cat swarm and Bayesian optimized DNN
Identifying cancer biomarkers is crucial for improving patient outcomes and reducing cancer-
related deaths. This research proposes BioSurv, a framework for biomarker identification …
related deaths. This research proposes BioSurv, a framework for biomarker identification …
A novel bio-inspired hybrid multi-filter wrapper gene selection method with ensemble classifier for microarray data
B Nouri-Moghaddam, M Ghazanfari… - Neural Computing and …, 2023 - Springer
Microarray technology is known as one of the most important tools for collecting DNA
expression data. This technology allows researchers to investigate and examine types of …
expression data. This technology allows researchers to investigate and examine types of …